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https://github.com/kazuph/mcp-docs-rag


https://github.com/kazuph/mcp-docs-rag

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README

          

# mcp-docs-rag MCP Server

RAG (Retrieval-Augmented Generation) for documents in a local directory

This is a TypeScript-based MCP server that implements a RAG system for documents stored in a local directory. It allows users to query documents using LLMs with context from locally stored repositories and text files.

## Features

### Resources
- List and access documents via `docs://` URIs
- Documents can be Git repositories or text files
- Plain text mime type for content access

### Tools
- `list_documents` - List all available documents in the DOCS_PATH directory
- Returns a formatted list of all documents
- Shows total number of available documents
- `rag_query` - Query documents using RAG
- Takes document_id and query as parameters
- Returns AI-generated responses with context from documents
- `add_git_repository` - Clone a Git repository to the docs directory with optional sparse checkout
- Takes repository_url as parameter
- Optional document_name parameter to customize the name of the document (use simple descriptive names without '-docs' suffix)
- Optional subdirectory parameter for sparse checkout of specific directories
- Automatically pulls latest changes if repository already exists
- `add_text_file` - Download a text file to the docs directory
- Takes file_url as parameter
- Uses wget to download file

### Prompts
- `guide_documents_usage` - Guide on how to use documents and RAG functionality
- Includes list of available documents
- Provides usage hints for RAG functionality

## Development

Install dependencies:
```bash
npm install
```

Build the server:
```bash
npm run build
```

For development with auto-rebuild:
```bash
npm run watch
```

## Setup

This server requires a local directory for storing documents. By default, it uses `~/docs` but you can configure a different location with the `DOCS_PATH` environment variable.

### Document Structure

The documents directory can contain:
- Git repositories (cloned directories)
- Plain text files (with .txt extension)

Each document is indexed separately using llama-index.ts with Google's Gemini embeddings.

### API Keys

This server uses Google's Gemini API for document indexing and querying. You need to set your Gemini API key as an environment variable:

```bash
export GEMINI_API_KEY=your-api-key-here
```

You can obtain a Gemini API key from the [Google AI Studio](https://makersuite.google.com/app/apikey) website. Add this key to your shell profile or include it in the environment configuration for Claude Desktop.

## Installation

To use with Claude Desktop, add the server config:

On MacOS: `~/Library/Application Support/Claude/claude_desktop_config.json`
On Windows: `%APPDATA%/Claude/claude_desktop_config.json`
On Linux: `~/.config/Claude/claude_desktop_config.json`

```json
{
"mcpServers": {
"docs-rag": {
"command": "npx",
"args": ["-y", "@kazuph/mcp-docs-rag"],
"env": {
"DOCS_PATH": "/Users/username/docs",
"GEMINI_API_KEY": "your-api-key-here"
}
}
}
}
```

Make sure to replace `/Users/username/docs` with the actual path to your documents directory.

### Debugging

Since MCP servers communicate over stdio, debugging can be challenging. We recommend using the [MCP Inspector](https://github.com/modelcontextprotocol/inspector), which is available as a package script:

```bash
npm run inspector
```

The Inspector will provide a URL to access debugging tools in your browser.

## Usage

Once configured, you can use the server with Claude to:

1. **Add documents**:
```
Add a new document from GitHub: https://github.com/username/repository
```
or with a custom document name:
```
Add GitHub repository https://github.com/username/repository-name and name it 'framework'
```
or with sparse checkout of a specific directory:
```
Add only the 'src/components' directory from https://github.com/username/repository
```
or combine custom name and sparse checkout:
```
Add the 'examples/demo' directory from https://github.com/username/large-repo and name it 'demo-app'
```
or add a text file:
```
Add this text file: https://example.com/document.txt
```

2. **Query documents**:
```
What does the documentation say about X in the Y repository?
```

3. **List available documents**:
```
What documents do you have access to?
```

The server will automatically handle indexing of documents for efficient retrieval.